from sklearn.neural_network import MLPClassifier
from sklearn.datasets import make_classification
from sklearn.model_selection import train_test_split
import numpy as np
import matplotlib.pyplot as plt
X, y = make_classification(n_samples=100, random_state=1)
X_train, X_test, y_train, y_test = train_test_split(X, y, stratify=y,random_state=1)
clf = MLPClassifier(random_state=1, max_iter=300).fit(X_train, y_train)
aa = clf.predict_proba(X_test[:1])

xx, yy = np.meshgrid(np.arange(1, 5, 1),
                     np.arange(2, 10, 1))
 